ATTACK VULNERABILITY OF COMPLEX NETWORKS BASED ON LOCAL INFORMATION

Abstract

We introduce a novel model for attack vulnerability of complex networks with a tunable attack information parameter. Based on the model, we study the attack vulnerability of complex networks based on local information. We employ the generating function formalism to derive the exact value of the critical removal fraction of nodes for the disintegration of networks and the size of the giant component based on local information. We show that hiding just a small fraction of nodes can prevent the breakdown of a network and that it is a cost-efficient strategy for enhancing the robustness of complex networks to hide the information of networks.